Hedging Effectiveness Research Articles

Asymmetry in Hedges, Safe Havens, Flights and Contagion: Unconditional Quantile Regression Approach

We examine the hedging/safe-haven ability of gold, the US dollar, bonds, crude oil, and Bitcoin against stocks using the unconditional quantile regression (UQR). We reveal that hedging (safe-haven) effect generally decreases (increases) with the quantiles of asset returns and find an asymmetric flight from stocks to the US dollar as well as asymmetric stock-gold, stock-bond, and stock-oil contagion. Finally, we find a connection between the asymmetric safe haven and asymmetric cross-asset flights/contagion. Therefore, investors seeking hedging and safe-haven assets and investigating flights or contagion should consider the feature of extremes of assets returns. JEL: C13; G11; G14

Time–frequency domain based optimization of hedging strategy: Evidence from CSI 500 spot and futures

Considering the significance of the frequency domain information in price series, we propose a decomposition-integration hedging model from the perspective of time–frequency domain to improve the hedging effectiveness and robustness. First, the returns series of spot and futures are decomposed and reconstructed into high frequency, medium frequency, and low frequency sequences to incorporate the frequency information into the hedging model. Then, we construct a model pool to fit the various characteristics of the data in each frequency domain and further extract the corresponding information. Finally, by taking four moments of investors risk appetite into consideration, the multi-objective optimization is employed to integrate the final hedging ratio. The empirical results indicate that the decomposition-integration hedging model is superior to the single time domain models in comprehensive evaluation indices. In addition, within a certain range of market fluctuations, the structure of our model has some characteristics that are compatible with reality. To recapitulate briefly, the hedging ratio of our model is mainly determined by the high frequency and medium frequency information under drastic market fluctuations. While when the market volatility is small, the hedging ratio largely depends on low frequency information.

Mitigating wildfire losses via insurance‐linked securities: Modeling and risk management perspectives

AbstractThis paper investigates the use of catastrophe (CAT) bonds as a risk management tool for wildfires. We introduce a set of Bayesian dynamic models designed to accurately represent wildfire losses, allowing a thorough examination of wildfire CAT bond pricing and hedge effectiveness. Our model captures crucial attributes of wildfire data, such as zero inflation, overdispersion, temporal fluctuations, and spatial dependence. Employing extensive quantitative analyses of US wildfire data, we highlight that CAT bonds can substantially mitigate tail risk associated with insurers' liability. Importantly, index‐based CAT bonds, drawing their payouts from aggregate wildfire losses over a larger geographical scope than an insurer's operational area, also provide effective hedges. Our research underscores the potential of wildfire CAT bonds as an enhancement to traditional reinsurance strategies, offering insurers an improved means to manage and mitigate wildfire exposures amidst inherent uncertainties.

Dynamic connectedness between energy markets and the Brazilian cash market: An empirical analysis pre‐ and post‐COVID‐19

AbstractBrazil's significant commodity production is internationally recognized, yet the absence of a mature futures market exposes it to price risks and international shocks. This study explores the dynamic connectedness between commodity futures and the Brazilian cash markets, using a time‐varying parameter vector autoregressive model. We also assess COVID‐19's impact on this connectedness. We find a significant influence of oil prices on Brazilian ethanol prices, and particularly emphasize the Heating Oil spillover effect on ethanol in the post‐COVID‐19 era. We also note the ascension of Brazilian soybean spot markets' international significance since 2017, amplifying their role in global grain price discovery. Finally, by computing hedge ratios and effectiveness between commodity futures contracts and Brazilian spot prices, our study reveals soybean cash price as the most effective hedge. These insights deepen comprehension of connectedness within Brazilian commodity markets, thereby guiding investors and policymakers in strategic energy policy decisions.

Operating Hedge and Gross Profitability Premium

ABSTRACTWe show theoretically that variable production costs reduce systematic risk of firms' cash flows if capital and variable inputs are complementary in firms' production and input prices are procyclical. In our dynamic model, this operating hedge effect is weaker for more profitable firms, giving rise to a gross profitability premium. Moreover, gross profitability and value factors are distinct and negatively correlated, and their premia are not captured by the capital asset pricing model (CAPM). We estimate the model by simulated method of moments, and find that its main implications for stock returns and cash flow dynamics are quantitatively consistent with the data.

The volatility spillover between battery metals and future mobility stocks: Evidence from the time-varying frequency connectedness approach

The transition to clean energy in the mobility sector, like other green solutions, necessitates a heightened dependence on critical minerals. The escalating demand for minerals, coupled with supply-side challenges, intensifies the price volatility of battery metals, which are crucial for ensuring sustainable production in the future mobility ecosystem. This paper examines the volatility connectedness between battery metals prices and stock prices of corporations engaging in future mobility between March 20, 2012, and March 2, 2022. We analyze the volatility of six base metals (i.e., aluminum, copper, lead, nickel, tin, and zinc), three minor metals (i.e., lithium, cobalt, manganese), and the Solactive Electric Vehicles and Future Mobility Index. We employ the novel frequency connectedness framework to identify the volatility spillovers and contagion among the variables across different investment horizons in a time-varying fashion. The future mobility equity market is a net volatility recipient, and copper and lithium are the dominant net volatility transmitters, emphasizing the pivotal role of battery metals in shaping the dynamics of the future mobility industry. We construct a minimum connectedness portfolio, offering significant hedging effectiveness for market participants. Finally, policy implications are discussed.

Forecasting the impact of financial stress on hedging between the oil market and GCC financial markets

PurposeThis paper investigates the predictive impact of Financial Stress on hedging between the oil market and the GCC stock and bond markets from January 1, 2007, to December 31, 2020. The authors also compare the hedging performance of in-sample and out-of-sample analyses.Design/methodology/approachFor the modeling purpose, the authors combine the GARCH-BEKK model with the machine learning approach to predict the transmission of shocks between the financial markets and the oil market. The authors also examine the hedging performance in order to obtain well-diversified portfolios under both Financial Stress cases, using a One-Dimensional Convolutional Neural Network (1D-CNN) model.FindingsAccording to the results, the in-sample analysis shows that investors can use oil to hedge stock markets under positive Financial Stress. In addition, the authors prove that oil hedging is ineffective in reducing market risks for bond markets. The out-of-sample results demonstrate the ability of hedging effectiveness to minimize portfolio risk during the recent pandemic in both Financial Stress cases. Interestingly, hedgers will have a more efficient hedging performance in the stock and oil market in the case of positive (negative) Financial Stress. The findings seem to be confirmed by the Diebold-Mariano test, suggesting that including the negative (positive) Financial Stress in the hedging strategy displays better out-of-sample performance than the in-sample model.Originality/valueThis study improves the understanding of the whole sample and positive (negative) Financial Stress estimates and forecasts of hedge effectiveness for both the out-of-sample and in-sample estimates. A portfolio strategy based on transmission shock prediction provides diversification benefits.

Hedging Strategies in Carbon Emission Price Dynamics: Implications for Shipping Markets

The European Union (EU) has agreed to gradually include shipping in the EU emissions trading scheme (EU ETS), which makes shipping companies vulnerable to carbon price fluctuations. The aim of this paper is to investigate the effectiveness of carbon and petroleum futures contracts in managing carbon and bunker risks. We examine the effectiveness of alternative hedging methods, including both static and dynamic approaches, to estimate optimal hedge ratios under single and composite cross-hedge settings. Our results show that carbon future contracts are important for hedging the carbon emission allowances price risk, and Brent oil futures are the most effective instrument for out-of-sample hedging of bunker prices. In addition, the hedging effectiveness indicates that conventional methods outperform the sophisticated models in terms of variance reduction. Our study offers new insights into how the carbon and bunker markets relate to a combination hedging in reducing the joint price risk, which can be used to promote risk management in the market.

Hedging Dynamic Fund Protection: A Static Versus Dynamic Comparison

The static nature of the downside protection offered by a standard Put option can motivate investors to use exotic option contracts like dynamic fund protection (DFP), which protects the underlying asset value throughout its life. DFP has a path-dependent payoff structure with its terminal payoff depending on the terminal asset price, the strike price and the minimum price level attained by the asset over the contract tenor. This makes DFP a contract strikingly similar to a Lookback Call option. In this article, we try to borrow the respective strengths from a dynamic and a static hedging strategy, formulate a semi-static hedging procedure for DFP and compare the hedging effectiveness of this procedure with a standard delta hedging strategy. Given the payoff resemblance between a DFP and a Lookback Call, we also seek to verify Tompkins (2002, Journal of Risk Finance, 3(4), 6–34) conclusion, which objectively shows that a dynamic procedure performs better in hedging a Lookback Call option both with and without transaction cost. Using simulated underlying price paths, we perform the delta hedging on DFP based on the closed-form pricing formula given by Gerber and Pafumi (2000, North American Actuarial Journal, 4(2), 28–37) and compare the hedge performance results with its static hedge counterpart.

Simulation Analysis of Equibiaxial Tension Tests for Rubber-like Materials.

For rubber-like materials, there are three popular methods of equibiaxial tension available: inflation tension, equibiaxial planar tension, and radial tension. However, no studies have addressed the accuracy and comparability of these tests. In this work, we model the tension tests for a hyperelastic electroactive polymer (EAP) membrane material using finite element method (FEM) and investigate their experimental accuracy. This study also analyzes the impact of apparatus structure parameters and specimen dimensions on experimental performances. Additionally, a tensile efficiency is proposed to assess non-uniform deformation in equibiaxial planar tension and radial tension tests. The sample points for calculating deformation in inflation tensions should be taken near the top of the inflated balloon to obtain a more accurate characteristic curve; the deformation simulation range will be constrained by the material model and its parameters within a specific limit (λ ≈ 1.9); if the inflation hole size is halved, the required air pressure must be doubled to maintain equivalent stress and strain values, resulting in a reduction in half in inflation height and decreased accuracy. The equibiaxial planar tension test can enhance uniform deformation and reduce stress errors to as low as 2.1% (at λ = 4) with single-corner-point tension. For circular diaphragm specimens in radial tension tests, increasing the number of cuts and using larger punched holes results in more uniform deformation and less stress error, with a minimum value of 3.83% achieved for a specimen with 24 cuts and a 5 mm punched hole. In terms of tensile efficiency, increasing the number of tensile points in the equibiaxial planar tension test can improve it; under radial tension, increasing the number of cuts and decreasing the diameter of the punched hole on the specimen has a hedging effect. The findings of this study are valuable for accurately evaluating various equibiaxial tension methods and analyzing their precision, as well as providing sound guidance for the effective design of testing apparatus and test plans.

Alarming contagion effects: The dangerous ripple effect of extreme price spillovers across crude oil, carbon emission allowance, and agriculture futures markets

The inherent financial interconnections between crude oil prices, carbon emission allowances, and agriculture commodity futures warrant a thorough investigation as fossil energy consumption, carbon emissions, and agriculture plants are three critical components of global environmental protection. This paper aims to quantify not only the normal (mean quantile) static and dynamic spillover effects among them in both time and frequency domains but also the more critical extreme spillovers that occur across various time horizons. Additionally, we explore the vital role of carbon futures in hedging risk and enhancing the performance of oil and agricultural portfolios. Empirical results indicate that, under extreme market situations, the total spillovers among oil, carbon, and agriculture commodity futures are much larger than those under normal conditions. Furthermore, soybean and corn are generally the most potent information transmitters over other futures in the time domain, while carbon emission allowance futures act as an obvious spillover receiver at both normal and extreme market conditions across various time frequencies. Both the total spillover and the net spillover are centered at a short-term frequency (i.e., one to four weeks). Finally, we find that carbon futures can contribute to improving the hedge effectiveness and performance of oil and agricultural portfolios. These findings have valuable implications for policymakers, relevant producers/consumers, as well as futures investors.

Extreme quantile spillovers and connectedness between oil and Chinese sector markets: A portfolio hedging analysis

Oil price instabilities have direct and heterogeneous implications for stock sector markets as a result of portfolio risk management and fund allocations. Previous studies have shown that the oil-stock market nexus is asymmetric and strongly vulnerable to international events. Using daily data of ten Chinese stock sector indices and the West Texas Intermediate crude oil futures over the period from July 2, 2007, to September 3, 2021, we examine the quantile return spillovers and interconnectedness between these markets using the approach of Ando et al. (2022), showing that return spillovers between the markets under investigation are more pronounced under bearish market conditions than during bullish ones. Major financial, political, energy, and COVID-19 pandemic events have magnified spillovers. Irrespective of the state of the market, oil is always a net receiver of return spillovers. Moreover, for all sectors other than materials, the sector that acts as a net receiver during bearish market conditions becomes a net contributor during bullish market conditions, and vice versa. During the COVID-19 period, the hedging technique was the most cost-effective. In the event of a global pandemic, the IT, financial, telecommunication, and energy sectors can benefit from oil's higher hedging effectiveness. Oil was a cheaper hedging asset during the pandemic, and it offered the highest hedging effectiveness to utilities before the outbreak and to the financial sector during the COVID-19 pandemic.

Which Commodity Sectors Effectively Hedge Emerging Eastern European Stock Markets? Evidence from MGARCH Models

This study aims at examining whether hedging emerging Eastern Europe stock markets with commodities sectors can help in reducing market risks and whether it has the same effectiveness among different sectors. As an attempt to achieve this goal, we opt for three types of MGARCH model. These are DCC, ADCC and GO-GARCH, which are used with each bivariate series to model dynamic conditional correlations, optimal hedge ratios and hedging effectiveness. Rolling window analysis is used for out-of-sample one-step-ahead forecasts from December 1994 to June 2022. The results have shown that the commodities sectors of industrial metals and energy represent the optimal hedging instruments for emerging Eastern Europe stock markets as they have the highest hedging effectiveness. Additionally, our empirical results have proved that hedge ratios estimated by the DCC and ADCC models are very similar, which is not the case for GO-GARCH, and that hedging effectiveness is preferably estimated by the ADCC model.

Plant growth stages and weather index insurance design

AbstractGiven the assumption that weather risks affect crop yields, we designed a weather index insurance product for soybean producers in the US state of Illinois. By separating the entire vegetation cycle into four growth stages, we investigate whether the phase-division procedure contributes to weather–yield loss relation estimation and, hence, to basis risk mitigation. Concretely, supposing stage-variant interaction patterns between temperature-based weather index growing degree days and rainfall-based weather index cumulative rainfall, a nonparametric weather–yield loss relation is estimated by a generalized additive model. The model includes penalized B-spline (P-spline) approach based on nonlinear optimal indemnity solutions under the expected utility framework. The P-spline analysis of variance (PS-ANOVA) method is used for efficient estimation through mixed model re-parameterization. The results indicate that the phase-division models significantly outperform the benchmark whole-cycle ones either under quadratic utility or exponential utility, given different levels of risk aversions. Finally, regarding hedging effectiveness, the expected utility ratio between the phase-division contract and the whole-cycle contract, and the percentage changes of mean root square loss and variance of revenues support the proposed phase-division contract.

Dynamic spillovers and portfolio implication between green cryptocurrencies and fossil fuels.

Are green investments decoupled from the dirty investment such as the fossil fuel markets? We address this issue by extending the literature on environmental, social, and governance (ESG) assets by examining the dynamic relationship between fossil fuels and digital ESG assets proxied by green cryptocurrencies using the TVP-VAR(Time-varying parameter vector auto regression) spillover framework. Furthermore, we analyze the hedging attributes of green cryptocurrencies and fossil fuels in a minimum connectedness framework. The main findings are as follows: First, green cryptocurrencies are the main shock transmitters in all asset systems. Second, the dynamic connectedness between green cryptocurrencies and fossil fuels increased during the COVID-19 and Russia-Ukraine conflicts. Third, green cryptocurrencies have shown considerable hedging effectiveness against the fossil fuels. Our study has important implications for investors, regulators, and policy makers, such as shifting to green cryptocurrencies, regulation of carbon footprint, and promoting eco-friendly assets.

Can China's national carbon trading market hedge the risks of light and medium crude oil? A comparative analysis with the European carbon market

The study explores whether China's national carbon market can hedge the risks of light and medium crude oil compared with the European carbon market, through the diversified and hedging portfolios estimated by the NAGARCHSK-Mixed Copula. The current work confirms the existence of conditional higher moments and asymmetric tail dependence structures in the crude and carbon markets. Furthermore, for all crude oil, although the China's carbon market is slightly inferior to the European carbon market in terms of hedging costs and stability, the hedging effectiveness of the former is better than that of the latter. And Oman crude oil gets better hedging protection from the carbon markets than Brent crude oil. Finally, the diversified portfolios obviously outperform the hedging portfolios in terms of hedging effectiveness.

The dynamic connectedness between private equities and other high-demand financial assets: A portfolio hedging strategy during COVID-19

In view of the need for portfolio diversification, we investigate the interlinkages between a private equity ETF and a set of high-demand asset classes including bonds, equities, crude oil, gold, commodities, currency, Bitcoin, and shipping within a spillover framework. For this objective, we apply the enhanced modification of the Diebold and Yilmaz approach for the period 1 January 2010 to 31 January 2023. The empirical findings indicate a modest degree of connectedness among the investigated markets, whereas volatility spillovers showed acceleration during tumultuous periods. In addition, we assess the capacity of private equities for hedging, for the whole sample period and during COVID-19 infectious disease, in order to suggest investors for potential portfolio restructures. Results demonstrate that the short position in the volatility of private equity ETF can result in strong hedging effectiveness for investors holding long positions in Bitcoin, shipping, bonds, and crude oil. JEL Classification: C32, C58, G11, G15

Minimizing the impact of geographical basis risk on weather derivatives

AbstractIn the last decade, the index-based weather products (also called weather derivatives) have been gaining attention in the climate resilience discussion. Weather derivatives are designed to help companies hedging against climate variability. These products, that can be market-traded or over-the-counter, compensate individuals based on a pre-defined weather index. Thus, pay-offs of a weather derivative depend on a weather index and not, as with traditional types of insurance, on the actual amount of money lost due to adverse weather. One of the major drawbacks that may prevent weather derivatives to catch on is the impact of the Geographical Basis Risk (GBR), that is the deviation of weather conditions at different locations. In fact, when the reference weather station is not located in the immediate vicinity of the site of interest the hedging effectiveness may be reduced. In this paper, we contribute to the existing literature on GBR by proposing an optimization method that may help in offering a tailored solution, while at the same time keeping a standardized instrument as a reference. Using a historical record of Italian temperatures, strikes for temperatures are the choice variables of a penalty function containing pay-offs of a reference station and all other stations. Further, altitude and latitude of meteorological stations are shown to be relevant predictors to explain GBR. This can be an interesting starting point for the design of weather derivatives, since, from a unique station where the “reference” derivative is priced, all the other stations may be easily settled.

State transformation of information spillover in asset markets and effective dynamic hedging strategies

This paper aims to develop a strategy to effectively and dynamically hedge risk by considering regime transitions of spillover effects between assets. We take six assets (stocks, bonds, real estate, currency exchange, crude oil, and gold) that are commonly used to construct investment portfolios as examples and analyze asset price data between September 2002 and January 2022. In doing so, we aim to examine the information spillover of different asset prices in both bear and bull market environments to determine whether state transformation affects dynamic hedging effectiveness. Using Markov-Switching Factor-Augmented Vector Autoregression (MS-FAVAR), we construct a regimen-switching model using variables from finance and economic conditions as endogenous variables to define the state transformations of the information spillover. Empirical results reveal that the MS-FAVAR model highlights changes in information spillover during a financial crisis/economic recession. Using dynamic-weighted hedging portfolios constructed with different indicators, we find that hedging effectiveness and volatility vary depending on the state of information spillover between different asset markets and that bear markets significantly impacted hedging effectiveness. Results also show that the panic sentiment (the fear index) explains the probability of a bear market. It is suggested that the state transformation of information spillovers should be monitored periodically, and hedging portfolios should be dynamically adjusted (bear or bull market) with shifting fear sentiment.

Pengaruh Profitabilitas, Hedging, dan Tingkat Utang terhadap Nilai Perusahaan Sub Sektor Batu Bara

Firm value is the standard price of a company that is considered feasible for potential investors. Firm value helps investors in assessing the performance of a company and also how the company's prospects are. As the value of the company increases, it can lead to an increase in the level of shareholder welfare. The object used in this study is a coal sub-sector company listed on the Indonesia Stock Exchange (IDX) for the 2018-2021 period. The utilization of Indonesian coal continues to increase, both industrial needs and for the fulfillment of people's daily lives. A decrease in coal prices can affect the financial performance of coal companies and by affecting the value of the company. The purpose of this study is to determine the effect of profitability, hedging, and debt level on company value in coal sub-sector companies listed on the Indonesia Stock Exchange (IDX) for the period 2018 to 2021 simultaneously and partially. This research uses data from the annual report and financial statements 2018-2021. The population in this study is coal sub-sector companies listed on the Indonesia Stock Exchange (IDX) for the period 2018 to 2021. In sample selection, this study used purposive sampling and obtained 13 companies with a research period of 4 years, so that 52 units of research samples were obtained. The data analysis method used is panel data regression analysis. Based on the results of the study, profitability, hedging, and debt levels simultaneously affect the value of the company. Partially, profitability has a significant positive effect on the value of the company, while hedging and debt levels do not have a significant effect on the value of the company.